The Git on IBM i Crisis
The reasons why IBM i teams struggle with Git workflows, that were designed for other platforms.
Manual Test Environment Setup
Days to prepare environments, full production data copies, shared bottlenecks
Environment Drift Disasters
Unnoticed differences between workspace, Git, and compiled objects cause failures
Complex Source Management
Difficult exports to Git from IBM i, encoding issues, multi-repository synchronization
Manual Integration Pain
Constant context switching to update Jira, Azure DevOps, ServiceNow manually
Repository Bottlenecks
Large Git operations block development, sequential processing kills productivity
High-Risk Deployments
All-or-nothing releases, difficult rollbacks, cross-platform coordination nightmares
Git Wasn't Built to Handle the IBM i Ecosystem
MDChange was designed to handle Git and everything on IBM i.
Traditional Data
Physical/logical files, multi-members, data areas, records
Files
Message, display, printer
SQL Entities
Tables, views, indexes, procedures, triggers, UDTs, rows
ILE/OPM
Modules, service programs, binding dirs, programs, packages
Job Management
JDs, subsystems, queues, workloads
Authorities
Public auth, auth lists, groups, IFS data
MDChange avoids both Git constraints and legacy limits by introducing an intelligent orchestration layer..
Organizations no longer face a false choice between legacy IBM i workflows and modern DevOps. See the features of MDChange for yourself below.
MDChange Devops Git Features
Everything You Need To Transform IBM i Git Development
Automated Git Branch Creation
Automated Generated Pull Requests
Post Merge Deployment Triggering
Simplified Export of Source & IFS Directories into Git
Granular or Bulk Git Commits Supported
Huge Git Repository Acceleration
Granular, Time-Sensitive Deployments
Feature-Branch Test Environments
Automatic Rollback and Risk Mitigation
Seamless Project Management Integration
Cross-Platform Deployment Guarantee
Git Workspace Synchronization & Visibility
The MDChange Advantage
Compare common IBMi DevOps Git problems with MDChange deliverables.
| Traditional Approach | With MDChange |
|---|---|
| Manual environment setup | Automated provisioning |
| Days to prepare test environment | Minutes to deploy feature branch |
| Manual data refresh | Automated data transformation |
| Full production data copies | Intelligent data subsetting |
| Shared environments = bottlenecks | Isolated environments = parallel work |
| "It works on my machine" syndrome | Consistent, reproducible environments |
| Manual object deployment | Automated, dependency-aware deployment |
| High risk of missing dependencies | Complete object tracking and management |
| Hours of data preparation per test | Test-ready data in minutes |
| Sequential repository operations | Parallel repository processing |
| Large repository clone bottlenecks | Distributed high-volume operations |
| Manual pull request creation | Automated pull requests from tasks |
| Manual deployment after merge | Triggered post-merge deployment |
| Complex export procedures for IBM i objects | Simplified export of source members & IFS |
| All-or-nothing commit strategy | Granular or bulk Git commits supported |
Ready to upgrade your IBM i Git DevOps?
Schedule a demo, get a free assessment, or start your journey today
